Automated Rheumatic Heart Disease Detection from Phonocardiogram in Cardiology Ward

Melkamu Hunegnaw Asmare, Melkamu Hunegnaw Asmare, Melkamu Hunegnaw Asmare, Frehiwot Woldehanna, Luc Janssens, Bart Vanrumste, Bart Vanrumste

2020

Abstract

Rheumatic Heart Disease (RHD) is a preventable and treatable form of cardiovascular diseases. It is also referred to as the ailment of the disadvantaged mainly affecting children and young adults. RHD is recognized as a global health priority by World Health Organization. This chronic heart condition silently deteriorates the normal function of the heart valves which can be detected as a heart murmur using a stethoscope. As the cardiac auscultation process is an elusive process, the clinician will always be tempted to refer the patient for expensive and sophisticated imaging procedures like echocardiography. In this study, a machine learning algorithm is developed to augment the limitation in the auscultation process and transform the stethoscope as a powerful screening tool. For this current study, an RHD heart sound data set is recorded from one hundred seventy subjects. A total of twenty-six features are extracted to model murmur due to RHD. Twenty-four classification and regression algorithms have been tested out of which the Cubic SVM has demonstrated superiority with a classification accuracy of 97.1%, with 98% sensitivity, 95.3 % of specificity 97.6% precision. The corresponding positive predictive values (PPV) are 96% and 97% for normal and RHD respectively. The results are based on data collected from a cardiology ward where there are more pathological cases than controls. Hence it is a valuable detection tool in a cardiology clinic. But in the future, integrating this machine learning algorithm with a mobile phone can be a powerful screening tool in places where access to echocardiography and cardiologist is difficult. Thus, it can then aid a timely, affordable and reliable detection tool allowing a non-medically trained individual to screen and detect RHD.

Paper Citation

in Harvard Style

Asmare M., Woldehanna F., Janssens L. and Vanrumste B. (2020). Automated Rheumatic Heart Disease Detection from Phonocardiogram in Cardiology Ward. In Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 5: Cognitive Health IT, ISBN 978-989-758-398-8, pages 839-844. DOI: 10.5220/0009367108390844

in Bibtex Style

@conference{cognitive health it20,
author={Melkamu Asmare and Frehiwot Woldehanna and Luc Janssens and Bart Vanrumste},
title={Automated Rheumatic Heart Disease Detection from Phonocardiogram in Cardiology Ward},
booktitle={Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 5: Cognitive Health IT,},
year={2020},
pages={839-844},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009367108390844},
isbn={978-989-758-398-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 5: Cognitive Health IT,
TI - Automated Rheumatic Heart Disease Detection from Phonocardiogram in Cardiology Ward
SN - 978-989-758-398-8
AU - Asmare M.
AU - Woldehanna F.
AU - Janssens L.
AU - Vanrumste B.
PY - 2020
SP - 839
EP - 844
DO - 10.5220/0009367108390844